Currently, with the popularity of digital cameras, mobile phones, cameras, and the like, a quantity of images that are generated is increasing. In particular, many photos may be photographed by a user during a tour. For example, a traveler in a package tour visits a lot of scenery spots every day. A lot of photos are stored in a camera, a mobile phone, or another photographing device at the end of the day. How to collate these photos is a problem. Because there is a large quantity of photos, to classify the photos manually is time-consuming and labor-intensive. In addition, photos of a same type are generated in different devices that have been used by a same user, and a large quantity of photos are generated in a same device that have been used by different users, leading to omissions during manual collation.
In addition, people like to photograph self-portraits when being alone, and like to photograph group photos when being in a tour together. When friends or family members usually share one camera during a tour, or when photos in multiple photographing devices are uploaded to a same album, the album includes photos of multiple users. When browsing the album, people can only search for the large quantity of photos for photos that they want. In a conventional album collation method, albums are usually separately generated according to photographing time and places of photos by using photographing time information and place information. However, by means of an existing album collation method, only a requirement of a user to classify photos according to time and places is met, and a requirement that a user browses multiple albums according to portrait classification cannot be met.